Scroll Top

Choosing Between a Cloud and On-Premises Option for Your Big Data Solution

Big data is no more just a buzzword. It has arrived. Organizations, large or small, have started realizing the benefits of analyzing large volumes of data for taking crucial business decisions. Big Data allows the creation of large data sets by accumulating data from multiple systems and providers. There is no denial that the information gathered from big data projects offers a lot of business benefits. However, to truly realize the benefits, organizations first need to design the right big data solution. One of the important decisions in the solution design is to determine whether to host it on-premises, in the cloud, or should the companies choose the hybrid option.

With the increasing popularity of Cloud Computing, companies are increasingly using the cloud to run their enterprise applications. A Verizon Report released in late 2015 found that more than 87 percent of enterprises are using the cloud to run mission-critical programs. A study by Intuit found that by 2020, around 78% of small businesses will be fully integrated in the cloud.

Traditionally, big data and analytics solutions have been running on-premises on the desktops and servers. However, the shift towards the Cloud is happening rapidly. Organizations have seriously started considering whether the Cloud investment can generate better RoI.  However, instead of blindly following one approach or the other, companies need to first identify the pros and cons, risks and rewards of each approach – strictly with respect to their own requirements.

Let us look at various factors which you need to consider while making the decision –


With the Cloud, typically the charges are based on the bandwidth usage. If your data analysis requires frequent movement of data in and out of the cloud, then you could incur higher bandwidth costs for the data transfer. For price sensitive projects, this could be a major factor to consider.


If your requirement is for real-time decision making, analysis of huge historical data or the data involves high bandwidth elements like audio and video data, then you need to confirm if the cloud environment creates latency or bottlenecks. If the delay in the data access or data processing is going to impact your decision making, then probably the cloud is not the right solution for you.


Highly secure data such as personal information, credit card information, or health records require careful handling. While over the past few years, the cloud has become more secure than most of the data centers, during the large scale migration of huge amount of data, a certain security issues could arise.  In such scenarios, organizations need to ensure that they implement strict governance policies and processes to reduce the security risks. Any failure in doing so could put the data in the shared infrastructure and pose a serious security issue.

Compliance and Regulations:

In some certain geographical locations, some industry sectors such as healthcare or financial services, there are strict government regulations on how the sensitive data should be stored and used. Companies in such verticals need to be extra careful about the security of their data, which is certain cases, could mean keeping it stored in private data centers.

Ease of Use:

Data Scientists and Big Data Management talent like ETL developers are rare to find and expensive resources. If the big data team has to spend a lot of time in working with multiple interfaces for various data repositories, they could end up wasting a lot of time. Their efficiency can reduce if the data integration requires dealing with multiple platforms. Organizations often forget to consider this issue, which can impact the overall costs and Return on Investment.


Not all the countries in the world enjoy high bandwidth and easy access into various public cloud providers. For global companies with remote sites in different locations, bandwidth constraints could pose issues with access to cloud resources.  In such situations, companies should go with private WAN connections which connect to the private data centers.


The Cloud better facilitates collaboration and improves business agility. A survey by Harvard Business Review Analytic Services found that for more than 72 percent of IT executives, collaboration is the top driver of cloud adoption. Cloud allows organizations to streamline their internal communications and also improve their customer communication through virtual deployments. With cloud deployment of big data analytics tools, organizations can quickly draw and analyze the data sets irrespective of their place of origination and foster cohesiveness in the organization.

Both on-premises and cloud data centers are here to stay and will continue to co-exist. There is no right or wrong answer for choosing the right option for your big data solution. It solely depends on your business needs, your data, your users, and your comfort levels with the cloud solution providers. Many a times, you might find a mix of all the solutions to be the most optimal option for you.

Leave a comment